We are happy to announce that the 10th DBpedia Community Meeting will be held in Amsterdam, Netherlands. During the SEMANTiCS 2017, Sep 11-14, the DBpedia Community will get together on the 14th of September for the DBpedia Day.

What cool things do you do with DBpedia? Present your tools and datasets at the DBpedia Community Meeting. Please submit your proposal in our form.

If you can’t stand it till the end of the SEMANTiCS, you can already participate in the workshop “Two worlds, one goal: A Reliable Linked Data ecosystem for media” held by DBpedia and Wolters Kluwer on the 11th of September. This half-day workshop aims at exploring major topics for publishers and libraries from DBpedia’s and Wolters Kluwer’s perspective. Therefore, both communities will dive into core areas like Interlinking, Metadata and Data Quality and address challenges such as fundamental requirements when publishing data on the web. Did we spark your interest? Check our detailed program here and get your ticket today.

After our 2nd Community Meeting in the US, we delighted the Irish DBpedia Community with the 9th DBpedia Community Meeting, which was co-located with the Language, Data and Knowledge Conference 2017 in Galway at the premises of the NUI Galway.

First and foremost, we would like to thank John McCrae (Insight Centre for Data Analytics, NUI Galway) and the LDK Conference for co-hosting and support the event.

The focus of this Community Meeting was the Irish DBpedia and Linked Data Community in Ireland. Therefore we invited local data scientists as well as European DBpedia enthusiasts to discuss the state of Irish Linked Data.

The meeting started with two compelling keynotes by Brian Ó Raghallaigh, Dublin City University and Logainm.ie, and Sharon Flynn, NUI Galway and Wikimedia Ireland. Brian presented Logainm.ie, a data use case about placenames in Ireland with a special focus on linked Logainm and machine-readable data.

Brian Ó Raghallaigh

His insightful presentation was followed by Sharon Flynn talking about Wikimedia in Ireland and the challenges of “this monumental undertaking” with particular reference to the Wikimedia Community in Ireland.

Sharon Flynn

For more details on the content of the presentations, follow the links to the slides.

Parallel sessions

As a regular part of the DBpedia Community Meeting we have two parallel sessions in the afternoon where DBpedia newbies can learn about what DBpedia is and how to use the DBpedia data sets.

Markus Freudenberg giving a DBpedia Tutorial

Participants who wanted to learn DBpedia basics joined the DBpedia Tutorial Session byMarkus Freudenberg (DBpedia Release Manager). The DBpedia Association Hour provided a platform for the community to discuss and give feedback.

Sebastian Hellman and Julia Holze @ the DBpedia Association Hour

Additionally, Sebastian Hellmann and Julia Holze, members of the DBpedia Association, updated the participants about the growing number of the DBpedia Association members, the formalized DBpedia language chapters, the established DBpedia Community Committee and they informed about technical developments such as the DBpedia API.

At this point, we also like to thank the ALIGNED project for the development ofDBpedia as a project use case and for covering parts of the travel cost.

Session about Irish Linked Data Projects

Chaired by Rob Brennan and Bianca Pereira, the speakers in the last session presented new Irish Linked Data Projects, for example GeoHive, BIOOPENER and the TCD Open Linked Data Engagement Fund Project. The following panel session gave DBpedia and Linked Data enthusiasts a platform for exchange and discussion. Outcome of this session was the creation of a roadmap for the Irish Linked Data with all participants.

Closing this session John McCrae announced that the next edition of the Language, Data and Knowledge (LDK) Conference is scheduled for 2019 in Germany. We at the DBpedia Association are now looking forward to welcome the LDK Community in Leipzig!

Social Evening Event

The Community Meeting slowly came to an end with our social evening event, which was held at the PorterShed in Galway. The evening session revolved around the topic How to exploit data commercially? and featured two short impulse talks. Paul Buitelaar started the session by presenting “Kibi”, which is an Open Source platform for Data Intelligence based on the search engine Elasticsearch. Finally, Sebastian Hellmann talked about “Improving the Utility of DBpedia by co-designing a public and commercial DBpedia API” (slides).

Summing up, the 9th DBpedia Community Meeting brought together more than 45 DBpedia enthusiasts from Ireland and Europe who engaged in vital discussions about Linked Data, DBpedia use cases and services.

Thanks Ireland and hello Amsterdam!

We are looking forward to the next DBpedia Community Meeting which will be held in Amsterdam, Netherlands. Co-located with the SEMANTiCS17, the Community will get together on the 14th of September on the DBpedia Day.

Sören Auer and the DBpedia Board members prepared a survey to assess the direction of the DBpedia Association. We wanted to know what the DBpedia Community thinks about DBpedia’s strategic priorities and how the funds of the DBpedia Association are be spent. Between February 2017 and April 2017, a total of 40 members of the DBpedia Community actively participated in the survey and voted as follows:

1. What should be the priorities of the DBpedia Association in the next year?

To overview the various priorities which were mentioned, the following digest illustrates the answers in four different groups. The most frequent answer was: to increase the data quality, followed by the enlargement of the DBpedia Community through broader dissemination.

2. What should be the priorities of the DBpedia Association in the next three years?

In contrast to question one, this one is based on the priorities the DBpedia Association focuses on during the next three years. As well as in the previous overview, the specified priorities are divided into four categories.

3. What is your main interest in DBpedia?

The chart above depicts the several main interests in DBpedia. The majority of participants have an “academic & professional” (45.7%) interest in DBpedia, followed by “professional” (28.6%) and “academic” (20.0%) interests. Only 2.9% of the answers are student-related interests.

4. How should the funds of the association be used?

With respects to “How should the funds of the association be used?”, most attendees chose “service provisioning”. The “development of new DBpedia features” was the second most popular choice. Nevertheless, also “Community building” and “release production” scored many votes.

5. How should the DBpedia Association collaborate with national/language chapters?

Agreeing on strategic goals; making sure that national contributions can be spread to other chapters, thus increasing the overall usability of DBpedia; keeping track of good practices

6. Should DBpedia open itself to contain and curate more data not directly extracted from Wikipedia?As the chart above clearly depicts, more than half of the participants are in favor of DBpedia comprising datasets not directly derived or extracted from Wikipedia. In contrast, 34.3% have the oppositional opinion and appreciate DBpedia focussing solely on data extraction from Wikipedia.

If yes, which other datasets should DBpedia prioritize for fusion to improve its coverage and quality?

7. Which of the following features do you consider most important?

The following diagram gives a review of particular features and their importance from the participants point of view. As the result of question one reveals, data quality is considered the most important issue by the survey participants (23.7%). The second most important features, with 17.2% each, are: the provision of datasets extracted from the Wikipedia article text, substantial collaboration/integration with WikiData and a provision of better search, respectively an exploration of user interfaces.

8. Any other question, feedback, opinion, ideas or suggestion you would like to send to the association.

KUTGW

Increased support of non-RDF publication formats is probably wise as an insurance policy that DBpedia will stay relevant.

In users mailing-list being more open-minded in an easy manner and always signalling provocative postings are welcome. And I fear it is a bit late for this survey, but better late than never, my greetings to all making some thoughts about this stuff.

DBpedia Spotlight should return Wikidata URIs by default, for stability

Use a richer ontology without contradictions, e.g. Book-Physical vs. Book-Conceptual Work

Thank you for your input and your participation! Your priorities and opinions are of vital importance for the success of DBpedia in the future. We will discuss the implementation of your answers during our next DBpedia Board Meetings in order to find a reasonable strategic direction of the DBpedia Association for the next years.

This release took us longer than expected. We had to deal with multiple issues and included new data. Most notable is the addition of the NIF annotation datasets for each language, recording the whole wiki text, its basic structure (sections, titles, paragraphs, etc.) and the included text links. We hope that researchers and developers, working on NLP-related tasks, will find this addition most rewarding. The DBpedia Open Text Extraction Challenge (next deadline Mon 17 July for SEMANTiCS 2017) was introduced to instigate new fact extraction based on these datasets.

We want to thank anyone who has contributed to this release, by adding mappings, new datasets, extractors or issue reports, helping us to increase coverage and correctness of the released data. The European Commission and the ALIGNED H2020 project for funding and general support.

You want to read more about the New Release? Click below for further details.[expander_maker id=”1″ more=”Read more” less=”Read less”]

Statistics

Altogether the DBpedia 2016-10 release consists of 13 billion (2016-04: 11.5 billion) pieces of information (RDF triples) out of which 1.7 billion (2016-04: 1.6 billion) were extracted from the English edition of Wikipedia, 6.6 billion (2016-04: 6 billion) were extracted from other language editions and 4.8 billion (2016-04: 4 billion) from Wikipedia Commons and Wikidata.

In addition, adding the large NIF datasets for each language edition (see details below) increased the number of triples further by over 9 billion, bringing the overall count up to 23 billion triples.

Changes

The NLP Interchange Format (NIF) aims to achieve interoperability between Natural Language Processing (NLP) tools, language resources and annotations. To extend the versatility of DBpedia, furthering many NLP-related tasks, we decided to extract the complete human- readable text of any Wikipedia page (‘nif_context’), annotated with NIF tags. For this first iteration, we restricted the extent of the annotations to the structural text elements directly inferable by the HTML (‘nif_page_structure’). In addition, all contained text links are recorded in a dedicated dataset (‘nif_text_links’).
The DBpedia Association started the Open Extraction Challenge on the basis of these datasets. We aim to spur knowledge extraction from Wikipedia article texts in order to dramatically broaden and deepen the amount of structured DBpedia/Wikipedia data and provide a platform for benchmarking various extraction tools with this effort.
If you want to participate with your own NLP extraction engine, the next deadline for the SEMANTICS 2017 is July 17th.
We included an example of these structures in section five of the download-page of this release.

A considerable amount of work has been done to streamline the extraction process of DBpedia, converting many of the extraction tasks into an ETL setting (using SPARK). We are working in concert with the Semantic Web Company to further enhance these results by introducing a workflow management environment to increase the frequency of our releases.

In case you missed it, what we changed in the previous release (2016-04)

We added a new extractor for citation data that provides two files:

citation links: linking resources to citations

citation data: trying to get additional data from citations. This is a quite interesting dataset but we need help to clean it up

In addition to normalised datasets to English DBpedia (en-uris), we additionally provide normalised datasets based on the DBpedia Wikidata (DBw) datasets (wkd-uris). These sorted datasets will be the foundation for the upcoming fusion process with wikidata. The DBw-based uris will be the only ones provided from the following releases on.

We now filter out triples from the Raw Infobox Extractor that are already mapped. E.g. no more “<x> dbo:birthPlace <z>” and “<x> dbp:birthPlace|dbp:placeOfBirth|… <z>” in the same resource. These triples are now moved to the “infobox-properties-mapped” datasets and not loaded on the main endpoint. See issue 22 for more details.

Major improvements in our citation extraction. See here for more details.

We incorporated the statistical distribution approach of Heiko Paulheim in creating type statements automatically and providing them as additional datasets (instance_types_sdtyped_dbo).

Upcoming Changes

DBpedia Fusion: We finally started working again on fusing DBpedia language editions. Johannes Frey is taking the lead in this project. The next release will feature intermediate results.

Id Management: Closely pertaining to the DBpedia Fusion project is our effort to introduce our own Id/IRI management, to become independent of Wikimedia created IRIs. This will not entail changing out domain or entity naming regime, but providing the possibility of adding entities of any source or scope.

RML Integration: Wouter Maroy did already provide the necessary groundwork for switching the mappings wiki to an RML based approach on Github. Wouter started working exclusively on implementing the Git based wiki and the conversion of existing mappings last week. We are looking forward to the consequent results of this process.

Further development of SPARK Integration and workflow-based DBpedia extraction, to increase the release frequency.

New Datasets

SDTypes: We extended the coverage of the automatically created type statements (instance_types_sdtyped_dbo) to English, German and Dutch.

Extensions: In the extension folder (2016-10/ext) we provide two new datasets (both are to be considered in an experimental state:

DBpedia World Facts: This dataset is authored by the DBpedia Association itself. It lists all countries, all currencies in use and (most) languages spoken in the world as well as how these concepts relate to each other (spoken in, primary language etc.) and useful properties like iso codes (ontology diagram). This Dataset extends the very useful LEXVO dataset with facts from DBpedia and the CIA Factbook. Please report any error or suggestions in regard to this dataset to Markus.

JRC-Alternative-Names: This resource is a link based complementary repository of spelling variants for person and organisation names. The data is multilingual and contains up to hundreds of variations entity. It was extracted from the analysis of news reports by the Europe Media Monitor (EMM) as available on JRC-Names.

Community

The DBpedia community added new classes and properties to the DBpedia ontology via the mappings wiki. The DBpedia 2016-04 ontology encompasses:

The editor community of the mappings wiki also defined many new mappings from Wikipedia templates to DBpedia classes. For the DBpedia 2016-10 extraction, we used a total of 5887 template mappings (DBpedia 2015-10: 5800 mappings). The top language, gauged by the number of mappings, is Dutch (648 mappings), followed by the English community (606 mappings).[/expander_maker]

SpringerNature for offering a co-internship to a bright student and developing a closer relation to DBpedia on multiple issues, as well as Links to their SciGraph subjects.

Kingsley Idehen, Patrick van Kleef, and Mitko Iliev (all OpenLink Software) for loading the new data set into the Virtuoso instance that provides 5-Star Linked Open Data publication and SPARQL Query Services.

OpenLink Software (http://www.openlinksw.com/) collectively for providing the SPARQL Query Services and Linked Open Data publishing infrastructure for DBpedia in addition to their continuous infrastructure support.

We are happy to announce that the 9th DBpedia Community meeting will be held in Galway, Ireland on June 21st 2017. DBpedia will be part of the Language, Data and Knowledge conference (LDK) in Galway. This new biennial conference series aims at bringing together researchers from across disciplines. The DBpedia Meeting is part of the conference and is scheduled for the last day.

Only few seats are left: So come and get your ticket to be part of the 9th DBpedia Community meeting in Galway.

The social event will be held in the evening (starting at 6pm) at the PorterShed around the topic How to exploit data commercially? featuring several short impulse talks. We still have some remaining slots and would welcome you to present your success stories as well as use cases, but also tell us about your problems regarding the commercialisation of data. If you are interested in presenting, please email dbpedia@infai.org.

New Internship Opportunity @

In conjunction withSpringer Nature,DBpedia offers a3 months internship at Springer Nature in London, UK and at DBpedia in Leipzig, Germany.

Internship Details

Position

DBpedia Intern

Main Employer

DBpedia Association

Deadline

June 30th, 2017

Duration

3 months/full-time, internship will starts in the second half of 2017

Location

50% in London (UK) and 50% in Leipzig (GER)

Type of students desired

Undergraduate, Graduate (Junior role)

Compensation

You will receive a stipend of 1300€ per month and additional reimbursement of your travel and visa costs (total up to 1000€)

The student intern will be responsible for assisting with mappings for DBpedia at SpringerNature. Your tasks include and are not restricted to improving the quality of the extraction mechanism of DBpedia scholarly references/wikipedia citations to Springer Nature URIs and Text mining of DBpedia entities from Springer Nature publication content.

GSoC students have finally been selected.

We are very excited to announce this year’s final students for our projects at the Google Summer of Code program (GSoC).

Google Summer of Code is a global program focused on bringing more student developers into open source software development. Stipends are awarded to students to work on a specific DBpedia related project together with a set of dedicated mentors during summer 2017 for the duration of three months.

For the past 5 years DBpedia has been a vital part of the GSoC program. Since the very first time many Dbpedia projects have been successfully completed.

In this years GSoC edition, DBpedia received more than 20 submissions for selected DBpedia projects. Our mentors read many promising proposals, evaluated them and now the crême de la crême of students snatched a spot for this summer. In the end 7 students from around the world were selected and will jointly work together with their assigned mentors on their projects. DBpedia developers and mentors are really excited about this 7 promising student projects.

You want to read more about their specific projects? Just click below… or check GSoC pages for details.[expander_maker id=”1″ more=”Read more” less=”Read less”] Ismael Rodriguez– Project Description: Although the DBPedia Extraction Framework was adapted to support RML mappings thanks to a project of last year GSoC, the user interface to create mappings is still done by a MediaWiki installation, not supporting RML mappings and needing expertise on Semantic Web. The goal of the project is to create a front-end application that provides a user-friendly interface so the DBPedia community can easily view, create and administrate DBPedia mapping rules using RML. Moreover, it should also facilitate data transformations and overall DBPedia dataset generation. Mentors: Anastasia Dimou, Dimitris Kontokostas, Wouter Maroy

Ram Ganesan Athreya – Project Description:The requirement of the project is to build a conversational Chatbot for DBpedia which would be deployed in at least two social networks.There are three main challenges in this task. First is understanding the query presented by the user, second is fetching relevant information based on the query through DBpedia and finally tailoring the responses based on the standards of each platform and developing subsequent user interactions with the Chatbot.Based on my understanding, the process of understanding the query would be undertaken by one of the mentioned QA Systems (HAWK, QANARY, openQA). Based on the response from these systems we need to query the DBpedia dataset using SPARQL and present the data back to the user in a meaningful way. Ideally, both the presentation and interaction flow needs to be tailored for the individual social network.I would like to stress that although the primary medium of interaction is text, platforms such as Facebook insist that a proper mix between chat and interactive elements such as images, buttons etc would lead to better user engagement. So I would like to incorporate these elements as part of my proposal.

Mentor: Ricardo Usbeck

Nausheen Fatma – Project discription:Knowledge base embeddings has been an active area of research. In recent years a lot of research work such as TransE, TransR, RESCAL, SSP, etc. has been done to get knowledge base embeddings. However none of these approaches have used DBpedia to validate their approach. In this project, I want to achieve the following tasks: i) Run the existing techniques for KB embeddings for standard datasets. ii) Create an equivalent standard dataset from DBpedia for evaluations. iii) Evaluate across domains. iv) Compare and Analyse the performance and consistency of various approaches for DBpedia dataset along with other standard datasets. v)Report any challenges that may come across implementing the approaches for DBpedia. Along the way, I would also try my best to come up with any new research approach for the problem.

Mentors: Sandro Athaide Coelho, Tommaso Soru

Akshay Jagatap – Project Description: The project aims at defining embeddings to represent classes, instances and properties. Such a model tries to quantify semantic similarity as a measure of distance in the vector space of the embeddings. I believe this can be done by implementing Random Vector Accumulators with additional features in order to better encode the semantic information held by the Wikipedia corpus and DBpedia graphs.

Mentors: Pablo Mendes, Sandro Athaide Coelho, Tommaso Soru

Luca Virgili – Project Description: In Wikipedia a lot of data are hidden in tables. What we want to do is to read correctly all tables in a page. First of all, we need a tool that can allow us to capture the tables represented in a Wikipedia page. After that, we have to understand what we read previously. Both these operations seem easy to make, but there are many problems that could arise. The main issue that we have to solve is due to how people build table. Everyone has a particular style for representing information, so in some table we can read something that doesn’t appear in another structure. In this paper I propose to improve the last year’s project and to create a general way for reading data from Wikipedia tables. I want to review the parser for Wikipedia pages for trying to understand more types of tables possible. Furthermore, I’d like to build an algorithm that can compare the column’s elements (that have been read previously by the parser) to an ontology so it could realize how the user wrote the information. In this way we can define only few mapping rules, and we can make a more generalized software.

Mentors: Emanuele Storti, Domenico Potena

Shashank Motepalli – Project Description: DBpedia tries to extract structured information from Wikipedia and make information available on the Web. In this way, the DBpedia project develops a gigantic source of knowledge. However, the current system for building DBpedia Ontology relies on Infobox extraction. Infoboxes, being human curated, limit the coverage of DBpedia. This occurs either due to lack of Infoboxes in some pages or over-specific or very general taxonomies. These factors have motivated the need for DBTax.DBTax follows an unsupervised approach to learning taxonomy from the Wikipedia category system. It applies several inter-disciplinary NLP techniques to assign types to DBpedia entities. The primary goal of the project is to streamline and improve the approach which was proposed. As a result, making it easy to run on a new DBpedia release. In addition to this, also to work on learning taxonomy of DBTax to other Wikipedia languages.

Mentors: Marco Fossati, Dimitris Kontokostas

Krishanu Konar – Project Description: Wikipedia, being the world’s largest encyclopedia, has humongous amount of information present in form of text. While key facts and figures are encapsulated in the resource’s infobox, and some detailed statistics are present in the form of tables, but there’s also a lot of data present in form of lists which are quite unstructured and hence its difficult to form into a semantic relationship. The project focuses on the extraction of relevant but hidden data which lies inside lists in Wikipedia pages. The main objective of the project would be to create a tool that can extract information from wikipedia lists, form appropriate RDF triplets that can be inserted in the DBpedia dataset.

Mentor: Marco Fossati [/expander_maker]

Congrats to all selected students! We will keep our fingers crossed now and patiently wait until early September, when final project results are published.

An encouraging note to the less successful students.

The competition for GSoC slots is always on a very high level and DBpedia only has a limited amount of slots available for students. In case you weren’t among the selected, do not give up on DBpedia just yet. There are plenty of opportunities to prove your abilities and be part of the DBpedia experience. You, above all, know DBpedia by heart. Hence, contributing to our support system is not only a great way to be part of the DBpedia community but also an opportunity to be vital to DBpedia’s development. Above all, it is a chance for current DBpedia mentors to get to know you better. It will give your future mentors a chance to support you and help you to develop your ideas from the very beginning.

Go on you smart brains, dare to become a top DBpedia expert and provide good support for other DBpedia Users. Sign up to our support page or check out the following ways to contribute:

Get involved:

Join our DBpedia-discussion-mailinglist, where we discuss current DBpedia developments. NOTE: all mails announcing tools or call to papers unrelated to DBpedia are not allowed. This is a community discussion list.

If you like to join DBpedia developers discussion and technical discussions sign up in Slack

Developer Discussion

Become a DBpedia Student and sign up for free at the DBpedia Association. We offer special programs that provide training and other opportunities to learn about DBpedia and extend your Semantic Web and programming skills

Do you want to stay informed about upcoming DBpedia events, releases and technical developments? Through the DBpedia newsletter you get the possibility to be always up to date and to provide feedback to us. Four times per year we will inform the DBpedia community about meetings, new collaborations and other topics related to DBpedia. So … Continue reading STAY TUNED AND SIGN UP FOR THE DBPEDIA NEWSLETTER→

DBpedia will participate for a fifth time in the Google Summer of Code program (GSoC) and now we are looking for students who will share their ideas with us. We are regularly growing our community through GSoC and can deliver more and more opportunities to you. We got excited with our new ideas, we hope you will get excited too!

What is GSoC?

Google Summer of Code is a global program focused on bringing more student developers into open source software development. Funds will given to students (BSc, MSc, PhD) to work for three months on a specific task. At first open source organizations announce their student projects and then students should contact the mentor organizations they want to work with and write up a project proposal for the summer. After a selection phase, students are matched with a specific project and a set of mentors to work on the project during the summer.

Sören Auer and the DBpedia Board members prepared a survey to assess the direction of the DBpedia Association. We would like to know what you think should be our priorities and how you would like the funds of the association to be used.

Your opinion counts – so please contribute actively in developing a better DBpedia. If you use DBpedia and want us to keep going forward, we kindly invite you to vote here: https://goo.gl/forms/rDqLcwL823Ok09Uw2

We will publish the results in anonymized, aggregated form on the DBpedia website.